AI may be high on the boardroom agenda—but many initiatives lose momentum after the initial proof-of-concept phase. Why?

Because there’s a critical disconnect between expectation and execution.

While leadership expects enterprise-grade, production-ready AI at speed, the teams on the ground face a different reality:

• It’s hard to find the right talent for the job—sometimes because there’s a hiring freeze, not enough skilled workers, or uncertainty about who exactly is needed.

• Teams aren’t always on the same page—business departments might not be involved enough or don’t fully support the project.

• The timing is off—projects and business goals aren’t aligned, so the value doesn’t show up when it’s needed.

Talent shortage among top obstacles in scaling

A 2024 MIT Sloan article quotes a study revealing that there's a big discrepancy in leadership's perception on this matter. 74% of CEOs think their teams are well-equipped for generative AI, but only 29% of their C-suite feels the same.

Deloitte reports that talent shortages remain a top barrier to scaling. Sure, proving a concept with AI can be fast. But taking it to production? That’s where the real work begins.

Succesfull AI implementation demands dedicated data and machine learning engineering, involvement of business units and their active collaboration with the project, and skilled AI product management to guide the process.

Where is the mistake?

Many companies still treat pilots like plug-and-play projects—without the right team, structure, or buy-in. And that’s a recipe for stalled outcomes and disappointed executives.

At ExpertHub, we help businesses bridge the gap in skills and understanding—so their promising AI pilot projects don’t just stop at testing, but turn into real, working solutions.

In the upcoming blog around the AI Talent in Enterprise we will discover what roles truly power the AI projects in business. Trust our hint: It’s not just about hiring one data scientist.

Have you experienced this expectation gap in your organization? How do you bridge it? Let us know at hello@joinexperthub.com or message us on LinkedIn!